For humans making, the car travel along the road lane line is easy as us humans can perceive the lanes as one of your common tasks, but when it comes to autonomous vehicles it is usually not the same case. For an autonomous, the main challenge is dealing with different varieties of roads, this paper discuses Indian roads specifically as on these roads sometimes the lane lines are not easily visible or they are not even marked. This paper discuses about the vision-based faction of algorithms that uses camera, it comprises of camera calibration using chessboard images to correct the distortion. Use of bird-eye view and conversion to different formats like HLS/RGB/HSV/YCrCb/Lab formats also using thresholding the warped images by trial-and-error thresholding, plotting Sobel-gradient with appropriate channels and in the end performing the lane pipelining to detect the lane lines in a video. For object detection, we have also use YOLO model. These techniques helped us to detect the lane lines. We used OpenCV computer vision framework that works upon the above functionalities using Python to obtain the results and to compare them.


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    Titel :

    Road Lane Line and Object Detection Using Computer Vision


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Shukla, Anupam (Herausgeber:in) / Murthy, B. K. (Herausgeber:in) / Hasteer, Nitasha (Herausgeber:in) / Van Belle, Jean-Paul (Herausgeber:in) / Sharma, Akshit (Autor:in) / Vir, Tejas (Autor:in) / Ohri, Shantanu (Autor:in) / Chowdhary, Sunil Kumar (Autor:in)


    Erscheinungsdatum :

    16.02.2023


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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